Category: IT Services
Location:
- Analyzes complex customer data to determine integration needs.
- Develops and tests scalable data integration/transformation pipelines using PySpark, SparkSQL, and Python.
- Contributes to the codebase through coding, reviews, validation, and complex transformation logic.
- Automates and maintains data validation and quality checks.
- Collaborates with FPA, data engineers, and developers to align solutions with financial reporting and business objectives.
- Participates in solution architecture and technical discussions, refining user stories and acceptance criteria.
- Utilizes modern data formats/platforms (Parquet, Delta Lake, S3/Blob Storage, Databricks).
- Partners with the product team to ensure accurate customer data reflection and provide feedback based on data insights.
- A Data Analytics Engineer with 5+ years of experience.
- Must have strong Python, PySpark, Notebook, and SQL coding skills, especially with Databricks and Delta Lake.
- Proven ability to build and deploy scalable ETL pipelines to cloud production environments using CI/CD.
- Experience with Agile/Scrum, data quality concepts, and excellent communication is essential.
- Cloud environment (Azure, AWS) and Infrastructure as Code (Terraform, Pulumi) experience beneficial.
- Telecoms industry or consulting experience, plus accounting knowledge, is a plus.
- J106998
Requirements
DetailsOriginally posted on Himalayas
